Data Analyst
Procter & Gamble
Job Overview
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Job Description
About the Data Analyst Role
Would you like to harness the power of data through breakthrough analytics, business consulting, and new capabilities to drive business results? At Procter & Gamble, the Analytics & Insights organization directly influences business strategy by delivering deep consumer, retailer, and market understanding through data science and advanced analytics.
Responsibilities
As a Data Analyst, you will be the go-to person for data analysis and big data applications. Your responsibilities include:
- Deliver insights using advanced analytic techniques and mining large datasets.
- Analyze market and share performance to identify trends and root-causes.
- Forecast growth opportunities and competitive threats for new market strategies.
- Enhance organizational knowledge with analytic capabilities.
What We Offer
You will receive assigned projects from Day 1, enjoy competitive salary and benefits, continuous coaching and mentoring, and the opportunity to work in a dynamic and respectful work environment.
Your Qualifications
A Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Applied Math, Statistics, Analytics, or related fields is required. You should have a passion for discovering insights, strong communication skills, good command of English, and experience with data science programming languages and analytics tools (SQL, R, Python, Power BI). Knowledge of Big Data ecosystems like Hadoop or Azure is an asset.
Hiring Process
The selection process consists of an application, online assessments, and interviews. Prepare accordingly by checking out the provided resources.
Key skills/competency
- Data Analytics
- Big Data
- SQL
- Python
- R
- Power BI
- Forecasting
- Market Analysis
- Communication
- Problem Solving
How to Get Hired at Procter & Gamble
- Customize Your Resume: Tailor skills and projects to analytics.
- Highlight Technical Skills: Emphasize SQL, Python, and R experience.
- Prepare for Assessments: Research data analytics case studies.
- Practice Interviews: Be ready to discuss past data projects.
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